A simulation based design flow for the development of heterogeneous systems is presented in this theses. A heterogeneous system is a huge system which includes several components like sensors, signal conditioning blocks, digital signal processing and actors. It can be simulated completely if special system models are developed. Additionally, more detailed models, which describe the components with higher accuracy, are needed during the development of these components. Mathematical characteristics to distinguish such models are derived in this theses. These characteristics define abstraction classes, which are not bound to a specific application domain: A mathematical meta model is defined instead. The proposed design flow for heterogeneous systems is based on consequential usage of transient time domain simulation and model based incremental validation. The significance of system simulation in this design flow is obvious. Maintenance and further development of the system models during the development process require a simulation system in which models of the different abstraction classes can be simulated together. Such a simulation system has been realized for this theses, it is adequate for simulating models from three different abstraction classes by combining a commercial VHDL-AMS simulation engine with a FPGA on a PCI card and a RAD tool. The FPGA is used to simulate digital components within real-time requirements; it can even lead to accelerated computation as it is shown in an example concerning image processing. The VHDL-AMS simulation engine is used to execute models of the sensors and models of the analog circuits. The importance of proper model design and of Refactoring of these models is shown with the virtual diving computer example. It is demonstrated how to divide the design task in small straightforward steps. Some steps are creative processes and others are Refactorings. Many of these Refactorings are described in the appendix of this work. These allow for a uncomplicated systematic transformation of existing descriptions in optimized ones.